effect of cross-functional information … · cross functional information sharing facilitates a...

International Journal of Business and Management Review

Vol.5, No.8, pp.12-29, October 2017

___Published by European Centre for Research Training and Development UK (www.eajournals.org)

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ISSN: 2052-6393(Print), ISSN: 2052-6407(Online)

EFFECT OF CROSS-FUNCTIONAL INFORMATION SHARING ON SUPPLY

CHAIN AGILITY OF COSMETICS MANUFACTURING FIRMS IN THE COUNTY

GOVERNMENT OF NAIROBI, KENYA

Pauline Jeruto Keitany, Dr. Josphat Kwasira, Dr. Rose Boit, Dr. Joel C. Chelule

Jomo Kenyatta University of Agriculture and Technology

ABSTRACT: Supply Chain Agility is widely regarded as a critical element that affects firms’

competitiveness at the strategic level. This is because firms with Supply Chain Agility have

better performance in responding to unforeseen events. The purpose of this study, was to assess

the effect of Cross Functional Information Sharing on Supply Chain Agility of Cosmetics

Manufacturing firms in the County Government of Nairobi. Cross Functional Information

Sharing is generally considered an enabler of a firm’s Supply Chain Agility. Information

Sharing has significant effects on the performance of Cosmetics Manufacturing Firms. These

trends have led to expanding the scale of procurement and reducing operating and purchase

costs in order to improve the responsiveness of the supply chain. Relational View theory,

Resource Based View Theory and Stategy, Structure and Performance Theory was adopted in

the study. Cross-sectional survey research design was used in the study. The target population

of the study was 714 employees working in the Cosmetic Manufacturing Firms in the County

Government of Nairobi, Kenya. A sample of 256 was selected from the target population using

a Multi Stage Sampling Technique. Both descriptive and inferential statistics was used to

analyse the collected data. The results indicates that there is a positive and statistically

significant correlation between Cross Functional Information Sharing and Supply Chain

Agility (r=.582, p < 0.01). This is a clear indication that any effort to improve the

communications channels making it more informative will lead to an increase in supply chain

agility. Therefore the study concludes that Cross functional information sharing is a pertinent

factor as it affects the Supply Chain Agility of Firms. With the growing technological advances

and the emergence of the global information infrastructure, firms should possess the suitable

competitive inter-organisational informational systems to enable them to achieve the rapid and

effective response to the customer needs and changing expectations.

KEYWORDS: Supply Chain agility, Cross-Functional Information Sharing, Competitiveness,

Performance

INTRODUCTION

In today’s competitive economy, focus has steadily increased on delivering value to the

customers. Globalization, technological change and demanding customers make the

marketplace more fiercely competitive than ever before (Fawcett et al., (2007). Concurrent to

the focus on customer value, the marketplace in which businesses operate today is widely

recognized as being complex and turbulent (Christopher, 2000). Hence, organizations are urged

to improve their operations, by becoming more interconnected and interdependent than before.

The expansion of supply chains, while enhancing profitability, customer responsiveness and

the ability to deliver value to the customers, has at the same increased the interconnections and

interdependencies among organizations. The global marketplace has become very volatile,

with customers demanding lower prices, faster delivery, and higher quality and increasing

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variety (Narasimhan & Das, (1999); Christopher, (2000); Powersox et al., (2001); Li & Lin,

(2006); Kisperska-Moron & de Haan, (2011).

Shortened product life cycles (Vonderembse et al., 2006), market uncertainty in the global

economic (Flint, 2004). According to Hervani et al., (2005), pressure from competitive forces

may force organization’s to reinvestigate how their supply chains are structured and managed,

in order to respond to the increasing market complexity, turbulence and uncertainty. In many

industries, complexity and uncertainty have increased to the point that competing

autonomously is no longer an option. The characteristics of products produced and processes

involved in manufacturing contribute to the complexity of the relationship. Speed, quality, and

flexibility are being emphasized as means of responding to the unique needs of customers and

markets. However, the core resource competencies required to realize the extended range of

objectives are often difficult to mobilize and retain by individual companies (Gunasekaran &

Yusuf, 2002).

Thus, in an agile supply chain, a high degree of cooperation between members of the supply

chain is required. It is recommended that the key to survival for organization’s dealing with

more innovative products such as cosmetics is creation of responsive or agile supply chains.

According to Yusuf et al., (1999), agility is a system with extraordinary capabilities to meet

the rapidly changing needs of the marketplace. Supply chain agility is the ability to respond

rapidly to changes in customer demand, both in product volume and variety (Christopher,

(2000); van Hoek et al., 2001). It is a system that responds quickly to new product models or

between product lines, ideally in real-time response to customer demand.

Purpose of the Research

The purpose of this study, was to assess the effect of Cross Functional Information Sharing on

Supply Chain Agility of Cosmetics Manufacturing firms in the County Government of Nairobi.

Cross Functional Information Sharing is generally considered an enabler of a firm’s Supply

Chain

Agility. Information Sharing has significant effects on the performance of Cosmetics

Manufacturing Firms. These trends have led to expanding the scale of procurement and

reducing operating and purchase costs in order to improve the responsiveness of the supply

chain. Consequently, its diversity in the service, price transparency, emphasis on fast,

convenient times and formats all working in the information technology (Sorescuet al., 2011).

Statement of the Problem

Cosmetic companies in Kenya compete in a market where rivalry is intense with a plethora of

brands and sub brands occupying both the lower and upper tiers of the price continuum. Despite

its fast growth, past research done on this sector reveals that there are quite a number of supply

chain challenges, which includes: securing a reliable internal operation capabilities, supply

chain disruptions, complexities in the supply chain, inconsistencies of quality supplies, poor

visibility of demand, lack of cooperation among supply chain members, conflicts among supply

chain members, lack of trust among supply chain members, short product life cycles and

competition from other supply chains Gordon Otila, (2011); Betty, CJ.(2014); Anderson M.

(2012). Cosmetics manufacturers are stressing flexibility and agility in order to respond to the

unique needs of customers and markets in real time. According to a research from the Future

Foundation (2015), more than 70% of the Kenyan Cosmetic Manufacturing Firms have not





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embraced technology. This is reflected by the 87% of the people who are still not able to shop

online, and more than 50% who are not able to shop cosmetics products via mobile phones due

to lack of technology. This has led to low productivity, poor quality products, inefficiency of

operations, and in the long run, impact on the competitive of the Industry. This calls for more

integration with supply chain partners who are able to cope with technological changes, provide

critical components of products and services and reduce uncertainty and respond to changes

accordingly. Cross fucntional Information Sharing is an important enabler of key processes in

an organisation and its supply chain as reflected in a developed economy. As such little

research has been done on this particular area, especially on the effect of Cross Functional

Information Sharing on Supply Chain agility of Cosmetics Manufacturing Firms. This becomes

quite fundamental because information sharing is regarded as an essential tool, commonly

accepted today that has significant effects on the productivity of Cosmetics industries and to

enhance the competitiveness of the economy of a developing country like Kenya. These effects

will only be fully realized if, and when, IT are widely spread and used. This becomes essential

to be addressed as Cross fucntional Information Sharing often enable processes across supply

chain and their implications for agility must be fully recognized and examined in a developing

economy. The study therefore was designed to fill this knowledge gap by assessing the Effect

of Cross-Functional Information Sharing on Supply Chain Agility in Cosmetics Manufacturing

Firms in the County Government of Nairobi, Kenya.

Research Hypothesis

Ho1: Cross Functional Information Sharing has no significant effect on the Supply Chain

Agility of Cosmetics Manufacturing Firms in the County Government of Nairobi.

Significance of the research

Cross functional information sharing facilitates a firm’s customer agility and competitive

activity. This is because Cosmetics Manufacturing organizations need to develop superior firm-

wide IT capabilities to manage their operations successfully and realize the agility. Customer

agility captures the extent to which a firm is able to sense and respond quickly to customer-

based opportunities for innovation and competitive action. Cross functional information

sharing plays a significant role in facilitating a “knowledge creating” synergy derived from

interaction between a firm’s web-based customer infrastructure and its analytical ability. A

typical premise is that greater IT investment enables such firms to be agiler (Lu and Ram,

2011).

LITERATURE REVIEW

Central to collaboration is the exchange of large amounts of information along the supply chain,

including planning and operational data, real time information, and communication.

Information is seen as the ‘glue’ that holds together the business structures that allow supply

chains to be agile in responding to competitive challenges. The backbone of the supply chain

business is IT which is used to acquire, process, and share information among supply chain

partners for effective decision making (Sanders & Premus, (2002); Paulraj et al., (2008). The

idea that information technology (IT) is a source of competitive advantage and fundamental to

a firm’s survival and growth is well-established (Prajogo & Olhager, 2012). Through

information technologies, coordination costs and the risks associated with inter-organizational





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relations can been reduced. Information technology allows buyers and suppliers to

communicate directly over data-rich, easyto-use information channels that reduce coordination

costs (Lewis & Talalayevsky, 2000).

Indeed, many organizations feel it necessary to engage in information technologies system such

as B2B e-commerce. If they do not, those competitors that do make use of such technologies

threaten to outpace them in efficiency gains and hence jeopardize their market position (Kaefer

& Bendoly, 2004). The strategic supply chain information allows supply chain partners in

making strategic decision in their operations (Li et al., 2006). Information sharing becomes

crucial in these turbulent economic times as it drives the firm into becoming a collaborative

structure. It requires firms to exchange strategic supply chain information apart from

transactional data, leading to improvement in the relationship and integration between the SC

partners ((Hsu et al., 2008).

According to Klein & Rai (2009), buyer and supplier strategic information flows positively

impact the relationship-specific performance of both sharing and receiving parties. Moreover,

quality of information sharing refers to the extent to which a firm shares a variety of relevant,

accurate, complete and confidential information in a timely manner with its supply chain

partners (Yen & Chae, 2006). While information sharing is important, the impact of it on SCM

depends on the quality with which it is shared (Holmberg, 2000). Given these predispositions,

levels of information sharing as well as quality of information shared become critical aspects

in deciding the supply chain success. The success of a company’s SCM depends upon the

accuracy and speed of the information provided by each business partner (Chong et al., 2009).

Information Sharing (IS) refers to the extent to which critical and proprietary information is

communicated among supply chain members with regards to market, product and customer

information (Mentzer et al., 2001). The Resource-Based View of the firm emphasizes on the

ability of firms in generating new knowledge and ability in facilitating information sharing.

Knowledge acquisition, assimilation, transformation and exploitation which are termed as

absorptive capacity in literature are important dimensions of organizational capability.

Therefore, cross functional information sharing with partners is considered as important

elements of supply chain capability. Wu et al., (2006) conceptualized information exchange as

one of the constructs representing supply chain capabilities. The effort in providing

information and making it visible to other parties in the supply chain allows for faster and

accurate business decisions that translates as a source of competitive advantage (Moberg et al.,

2003).

Information sharing is regarded as the terminator of “bullwhip effect” (Fiala, 2005), that

reduces the total cost of the supply chain in delivering efficient supply chain performance

(Gavirneni, 2006). This implies that a successful sharing of useful information between the

supply chain partners can result in a reduction in inventory and manufacturing cost, better

understanding of customer needs, and faster response to market changes (Li et al., 2006).

Cross-Functional Information sharing requires firms to exchange strategic supply chain

information apart from transactional data, leading to improvement in the relationship and

integration between the SC partners. Information Sharing (IS) refers to the extent to which

critical and proprietary information is communicated among supply chain members with

regards to market, product and customer information (Mentzer et al., 2001).

A key characteristic of supply chain agility is the instant availability of information to manage

an ’on demand’ business operation. IS integration provides the basis for information sharing

and exchange of organizations (Auramo et al., 2005). Cross functional information sharing





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requires the integration of communication, data and application (Muller et al., 2007) to enable

consistent and real-time connectivity among function units across supply chains (Rai et al.,

2006). Information sharing integration within and among organizations enables them to capture

data on demand, leading to customer-focused supply chains (Christopher, 2000). Firms are

more likely to gain competitive advantage through fast delivery and product variety rather than

price. Therefore, the effectiveness of supply chains can be measured by its responsiveness (Lee

& Billington, 1992).

RESEARCH METHODOLOGY

Cross-sectional survey research design was used in the study. According to Saunders & Lewis

(2009), survey is a popular and common method in business and management research. It is

used to answer who, what, where and how questions. Further, survey design allowed for

collection of large amount of data from a sizeable population in a highly economical way. A

cross-sectional study design is used when the purpose of the study is descriptive, often in the

form of a survey (Crewell, 2003). Orodho and Kombo (2002) asserts that the central feature of

survey is that it allows the collection of a large amount of data from a sizeable population in a

highly economical way and gives the researcher control over the research process.

The target population of the study consisted of 714 employees working in the Cosmetic

Manufacturing Firms in County Government of Nairobi. The study adopted Yamane (1967)

formula for calculating sample size.to determine the sample size. The sample size for the study

therefore, was 256 respondents. Purposive and Simple random sampling methods was used.

Structured and unstructured questionnaires was developed basing on the objectives of the

study. The researcher used questionnaire and interviews to collect primary data. Quantitative

data was analyzed using descriptive statistical measures such as, mean, standard deviation and

variance to give a glimpse of the general trend with the aid of Statistical Package for Social

Scientist (SPSS) version 24. Inferential statistics was also applied in the study.

RESEARCH FINDINGS

The researcher administered questionnaires to 256 respondents who were sampled out as per

the methodology described in the previous chapter. 210 duly filled questionnaires were

returned. This represents a response rate of 93.75 %. According to Sekaran, (2006), a response

rate of 30% is considered acceptable for surveys. Thus, the response rate achieved in this study

can be considered sufficient to give the findings adequate reliability. From the results, majority

56.7% (119) were Male and 43.3% (91) were Female. This is a clear indication that male

individuals form the backbone of the cosmetic manufacturing companies. The study also

sought to determine respondent’s education level. The findings of the study indicate 2.9% (6)

of the respondents who were picked had secondary education, 31.0% (65) of the respondents

who were picked were certificate/diploma holders, and 52.9% (111) were graduate. While the

rest 13.3% (28) were Masters Holders. This was an indication that most of the employees had

relevant skills needed in the cosmetic manufacturing firms. The study sought to find out the

duration the respondents have been working since they were employed. It is evident from the

findings that majority 42.9% (90) of the respondents have been working in the Firm for a period

of between 3-6 years, 16.2% (34) have worked in the firms for a period of between 6-10 years.





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Those who have worked in the firm for over 10 years were 7.1% (15), 30% (63) have worked

in the firm for a period between 1-3 years whereas 3.8% (8) are the respondents who have less

than one year experience working in the Cosmetics Manufacturing Firm.

This is an indication that most of the respondents have been working for a length of period

hence were able to provide relevant and reliable information for the study. This also implies

that Cosmetics Manufacturing Firms in Nairobi had attracted and retained skilled labour as

evidenced by their experience and the duration of the employee in the job. Length of service

with the cosmetic company was important in order to determine the respondent’s level of

understanding regarding internal information pertinent to the company. The period worked in

the firm is usually in line with experience, responsibility and skills of the business person

(Karanja, 2011). The study also sought to ascertain how long the Cosmetics Manufacturing

Firms have been in existence. The study found that most firms 32.4% (68) have been in

existence for a period of 5-10 years, 22.9% (48) of the firms have been in existence between

11-15 years, 17.1% (36) of the firms have been in existence between 16-20 years, 15.7% (33)

of the firms have been in existence for 20 years and above whereas those of have existed for

less than 5 years were 11.9% (25). This is a clear indication that the information that was

captured was sufficient since most of the firms sampled had existed for a long period that is 5-

10 years.

Effect of Cross Functional Information Sharing and Supply Chain Agility

The study sought to determine on the effect of Cross Functional Information Sharing on Supply

Chain Agility. The results are presented in Table 4.1

Table 4.1: Descriptive Statistics for Cross Functional Information Sharing

Cross Functional

Information Sharing

Statements

SD

(%)

D

(%)

N

(%)

A

(%)

SA

(%)

N Mi

n

Max Mean Std

Dev

Up to date data and

information of the

company is always

readily available for

all the parties

2.9 5.7 20 53.3 18.1 210 1 5 3.78 0.90

7

We inform supply

chain partners in

advance of changing

needs

0 1.9 11.9 60.5 25.7 210 2 5 4.10 0.66

7

We keep each other

informed about events

or changes that may

affect the other party

0 3.3 14.8 44.8 37.1 210 2 5 4.16 0.79

4

Unforeseen challenges

are properly

communicated to our

suppliers

0.5 3.3 20.0 44.3 31.9 210 1 5 4.04

0.83

5





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Exchange of

information takes

place frequently,

and/or in a timely

manner

0 2.9 13.3 58.1 25.7 210 2 5 4.07

0.70

9

Information exchange

between us and our

supply chain partners

is always timely, fast

and accurate

1.9 1.0 16.2 50.0 31.0 210 1 5 4.07 0.824

Information

exchanged between us

and our supply chain

partners is often

adequate

1.0 4.3 17.2 50.2 27.3 210 1 5 3.99 0.841

Information



partners is often

reliable

0.5 1.4 14.3 47.1 36.7 210 1 5 4.18 0.761

Information



partners is quite

complete

1.4 3.3 19.5 48.1 27.6 210 1 5 3.97 0.858

Grand Mean = 4.04

Valid N (Listwise) =

210

The findings reveal that the respondents admitted (Mean =4.18; Std Dev =0.761) that

Information exchanged between them and their supply chain partners is often reliable.

Respondents were also in agreement (Mean =4.16; Std Dev =0.794) that they keep each other

informed about events or changes that may affect the other party. The findings further indicated

(Mean =4.10; Std Dev =0.667) that they inform their supply chain partners in advance of

changing needs. The respondents also concurred (Mean =4.07; Std Dev =0.824) with the

statement that Information exchanged between us and our supply chain partners is often

adequate. Findings also revealed that respondents were in agreement (Mean =4.07; Std Dev

=0.709) that exchange of information takes place frequently, and/or in a timely manner.

Findings further indicated the respondents were in agreement (Mean =4.06; Std Dev =0.813)

with the statement that their firm provides substantial information to the parties in the

relationship which is of great use in order to improve their products. In addition, the

respondents agreed (Mean =4.04; Std Dev =0.709) that unforeseen challenges are properly

communicated to our suppliers. Further, findings revealed (Mean =3.99 Std Dev =0.841) that

information exchanged between us and our supply chain partners is often adequate.

Furthermore, respondents agreed (Mean =3.97 Std Dev =0.858) that Information exchanged

between us and our supply chain partners is quite complete. Finally, findings revealed that





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(Mean =3.78 Std Dev =0.907) up to date data and information of the company is always readily

available for all the parties. The respondents generally agreed on the statements pertaining to

cross functional information sharing.

Supply Chain Agility

The study also sought to determine the respondent’s level of agreement with effect of Supply

Chain Agility on the performance of Cosmetics Manufacturing Firms in the County

Government of Nairobi. Table 4.2 shows the findings.

Table 4.2: Descriptive Statistics for Supply Chain Agility


Statement

SD

(%)

D

(%)

N

(%)

A

(%)

SA

(%)

N Mi

n

Ma

x

Mea

n

Std

Dev

Our company is able to

survive and prosper in a

competitive environment

of continuous and

unpredictable changes by

reacting quickly and

effectively to changing

markets

3.3 1.9 9.0 63.3 22.

4

210 1 5 3.99 0.832

Our firm is able to

proactively establish

virtual manufacturing with

an efficient product

development system so as

to meet changing market

requirements

1.0 3.8 13.

8

52.4 29.

0

210 1 5 4.29 3.609

We have the capability

both internally and in

conjunction with our key

suppliers to adapt and

respond in a speedy

manner to changes as well

as potential or actual

disruptions

0 2.9 16.

2

48.1 32.

9

210 2 5 4.11 0.772

Supply chain agility has

led to improved delivery

and reliability

hence competitiveness of

the firm

1.9 1.4 13.

3

48.1 35.2 210 1 5 4.13 0.837


led to products and

services with high

information and value

adding content

0 1.9 9.5 53.8 34.8 210 2 5 4.21

0.689

Our firm through supply

chain agility has led to

0.5 1.4 15.

2

45.2 37.6 210 1 5 4.18

0.774





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customer satisfaction in a

turbulent and volatile

market hence improved

responsiveness to customer

needs.


led to agile manufacturing

that in turn enables the firm

to meet changing market

requirements with high

quality goods

on a consistent basis

0.5 1.0 13.

8

51.0 33.8 210 1 5 4.16 0.729

The firm is always ready to

produce a broad range of

low cost, high quality

products with short lead

times in varying low sizes,

built to individual customer

specifications

1.0 2.9 11.

9

45.2 39.0 210 1 5 4.19 0.824

We are always ever ready

to deliver value to the

customer in an

environment where

customer requirements are

becoming more customized

0.5 2.4 8.1 48.6 40.5 210 1 5 4.26 0.747

There is instant availability

of information to manage

an on demand business

operation in the

organization

1.0 1.4 13.

3

57.1 27.1 210 1 5 4.08 0.737

Grand Mean = 4.13

Valid N (Listwise) = 210

The results indicates that respondents were in agreement (Mean =4.29; Std Dev =3.609) that

Our firm is able to proactively establish virtual manufacturing with an efficient product

development system so as to meet changing market requirements. Further, the respondents

concurred (Mean =4.26; Std Dev =0.747) that we are always ever ready to deliver value to the

customer in an environment where customer requirements are becoming more customized. It

is also evident from the results that Supply Chain Agility (Mean =4.21; Std Dev =0.689) has

led to products and services with high information and value adding content. In addition,

respondents agreed (Mean =4.19; Std Dev =0.824) that the firm is always ready to produce a

broad range of low cost, high quality products with short lead times in varying low sizes, built

to individual customer specifications. The respondents also agreed (Mean =4.18; Std Dev

=0.774) with the statement that our firm through supply chain agility has led to customer

satisfaction in a turbulent and volatile market hence improved responsiveness to customer

needs. Further, respondents concurred that Supply Chain Agility (Mean =4.16; Std Dev

=0.729) has led to agile manufacturing that in turn enables the firm to meet changing market

requirements with high quality goods on a consistent basis.





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Findings also indicated that Supply Chain agility (Mean =4.13; Std Dev =0.837) has led to

improved delivery and reliability hence competitiveness of the firm. It is also evident from the

results (Mean =4.11; Std Dev =0.772) that the respondents agreed that the firms have the

capability both internally and in conjunction with our key suppliers to adapt and respond in a

speedy manner to changes as well as potential or actual disruptions.Findings further indicates

that the respondents agreed (Mean =4.08; Std Dev =0.737) that there is instant availability of

information to manage an on demand business operation in the organization. Finally, the

respondents also agreed (Mean =3.99; Std Dev =0.832) with the statement that our company is

able to survive and prosper in a competitive environment of continuous and unpredictable

changes by reacting quickly and effectively to changing markets. Supply chain agility

represents the speed with which a firm’s internal supply chain functions can be adapt to

marketplace changes (Swafford et al., 2008). It is captured by manufacturing lead time, new

product introductions, development cycle time, delivery capability and responsive to market

changes. Overall, the respondents agreed on the statements pertaining to supply chain agility.

The Moderating effect of Technological Engagement on the relationship between Cross

Functional Information Sharing and Supply Chain Agility

The study further sought to assess the Moderating effect of Technological Engagement on the

Relationship between Cross functional Information Sharing and Supply Chain Agility of

Cosmetics Manufacturing Firms in the County Government of Nairobi. The results are

presented in Table 4.3.

Table 4.3: Descriptive Statistics for Technological Engagement

Technological

Engagement Statements

SD

(%)

D

(%)

N

(%)

A

(%)

SA

(%)

N Mi

n

Max Mean Std

Dev

Information Technology in

our firm has quite

improved the quality of

communication

1.4 1.4 7.6 53.8 35.7 21

0

1 5 4.21 0.76

0

Adoption of technology

has led to added value to

supply chain functions

through greater efficiency

and information

transparency.

0 1.0 10.0 51.0 38.1 21

0

2 5 4.26 0.67

3

Technology engagement in

our firm has led to better

coordination and

integration of information

flows and activities within

and between boundaries.

0.5 0 9.0 43.8 46.7 21

0

1 5 4.36 0.68

6

Adoption of technology

has led to the development

of new services, products,

functions and formation of

alliances.

0.5 1.0 11.9 41.0 45.7 21

0

1 5 4.30 0.75

3





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Our firm's use of IT has

improved our transaction

speed thus reduced lead

time

0 0 5.7 44.8 49.5 21

0

3 5 4.44 0.60

2

Technology engagement in

our firm has led to

reduction in costs,

increased efficiency across

the extended supply

chain and enhanced work

flow

0.5 1.4 6.7 52.4 39.0 21

0

1 5 4.28 0.69

3

The use of technology in

our firm has led to

improved service delivery

to our

0.5 0.5 7.1 49.5 42.4 21

0

1 5 4.33 0.67

2

Technology use in our firm

has allowed planning,

tracking and estimating

lead times based on real

data

0 2.4 18.6 39.5 39.5 21

0

2 5 4.16 0.80

8

Grand Mean = 4.29

Valid N (Listwise) = 210

The findings reveal that the respondents were in agreement (Mean =4.44; Std Dev =0.602) that

Our firm's use of IT has improved our transaction speed thus reduced lead time. Respondents

were also in agreement that Technology Engagement (Mean =4.36; Std Dev =0.686) in our

firm has led to better coordination and integration of information flows and activities within

and between boundaries. The respondents also concurred with the statement that the use of

Technology in our firm (Mean =4.33; Std Dev =0.672) has led to improved service delivery to

our customers.

Further, findings reveal that respondents agreed that adoption of technology (Mean =4.30; Std

Dev =0.753) has led to the development of new services, products, functions and formation of

alliances. It is also evident from the findings that technology engagement in the firms (Mean

=4.28; Std Dev =0.693) has led to reduction in costs, increased efficiency across the extended

supply chain and enhanced work flow. Further, the respondents agreed (Mean =4.26; Std Dev

=0.673) with the statement that Adoption of technology has led to added value to supply chain

functions through greater efficiency and information transparency. Respondents also concurred

(Mean =4.21; Std Dev =0.760) that Information Technology in our firm has quite improved

the quality of communication. Finally, the respondents were in agreement (Mean =4.16; Std

Dev =0.808) that Technology use in our firm has allowed planning, tracking and estimating

lead times based on real data. Overall, the respondents agreed on the information pertaining to

Technological Engagement.





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Correlation between Cross Functional Information Sharing and Supply Chain Agility

The relationship between Cross Functional Information Sharing and Supply Chain Agility was

also examined. The results of correlation analysis are presented in Table 4.3.

Table 4.31: Correlation between Cross Functional Information Sharing and Supply

Chain Agility

Variable Supply Chain Agility

Cross Functional

Information sharing

Pearson Correlation .582**

Sig. (2-tailed) .000

N 210

** Correlation is significant at the 0.01 level (2-tailed).

The results indicates that there is a positive and statistically significant correlation between

Cross Functional Information Sharing and Supply Chain Agility (r=.582, p < 0.01). This is a

clear indication that any effort to improve the communications channels making it more

informative will lead to an increase in supply chain agility.

Chi Square Test

To examine the strength of associations between the bivariate categorical variables, a Chi-

Square test for association was done for the independent variables, dependent and moderating

variable.

Table 4.42: Chi- Square Tests between Cross Functional Information Sharing and


Value Degree of Freedom Asymptotic

Significance (2-sided)

Pearson Chi Square 1470.099a 600 .000

Likelihood Ratio 393.586 600 1.000

Linear-by- Linear Association 69.894 1 .000

Sample size 207

Strength of the Associations between Cross Functional Information Sharing and Supply Chain

Agility was also tested. Table 4.3 shows a Chi-Square value = 1470.099, p = 0.000. The p

value is less than 0.05 and hence there is a statistically significant association between Cross

Functional Information Sharing and Supply Chain Agility. This is a clear indication that

information technology is a source of competitive advantage and fundamental to firm’s

survival and growth is well established.

Regression Analysis

Multiple regression analysis was conducted so as to determine the relationship between supply

chain agility, Technological engagement and the independent variables





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Model definitions based on Moderated Multiple Regression Analysis

Regression model were generated at two levels. The first level without the interaction term and

the second level with the moderator.

Relationship between Cross Functional Information Sharing and Supply Chain Agility

in Cosmetics Manufacturing Firms in the County Government of Nairobi, Kenya

Table 4.5 show two model summary for Cross Functional Information Sharing when moderator

is included and when the effect of the moderator is not included.

Table 4.5: Regression Model summary for Cross Functional Information Sharing

Std. Error Change

Statistics

Adjusted of the R Square F

Sig. F

Model R R2

R Square Estimate Change Change Df1 Df2 Change

1 .582a

.339 .336 .374 .339 105.272 1a

205 .000

2 .670b .449 .443 .343 .110 40.531 1b 204 .000

a. Predictor (Constant), Cross Functional Information Sharing b. Predictor (Constant),

Cross Functional Information Sharing * Technological Engagement

Model 1 shows there is a positive relationship between Cross Functional Information Sharing

and Supply Chain Agility (R = 0.582, R2 = 0.339) and (F (1,205) = 105.272, p=0.000). The R2

explains the variations in the dependent variable that can be explained by the independent

variables. R2 of 0.339 indicates that 33.9% of the variations in the Supply Chain Agility of

cosmetics manufacturing firms can be accounted for by Cross Functional Information Sharing.

Model 2 shows the results after the interaction of the moderator (Cross Functional Information

Sharing*Technological Engagement) was introduced in the model. The results shows there is

a positive relationship between Cross Functional Information Sharing and Supply Chain

Agility in cosmetics manufacturing firms with (R = 0.670, R2 = 0.449) and (F (1,204) = 40.531,

p=0.000). An R2 of 0.449 indicates that 44.9% of the variations in the Supply Chain Agility in

cosmetics manufacturing firms can be accounted for by Cross Functional Information Sharing

*Technological Engagement.

The inclusion of the interaction term resulted in a R2 change of .110 which indicates that the

moderating effect explains 11% of the variation in the Supply Chain Agility above and beyond

the variation explained by the Cross Functional Information Sharing. The results obtained

shows a significant presences of moderating effect of Technological Engagement on the

relationship between Cross Functional Information Sharing and Supply Chain Agility in

cosmetics manufacturing firms in the county government of Nairobi, Kenya. Table 4.6 shows

the significance test results with two models, the model with the inclusion of the interaction

term and the other model without the moderator.





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Table 4.6: Significance Test Results for Cross Functional Information Sharing

Unstandardized

Coefficients

Standardized

Coefficient

Beta

Model B Std. Error T Sig

1 (Constant) 1.803 .229 7.890 .000

Cross Functional

Information Sharing .577 .056 .582 10.26 0

.000

2 (Constant) .819 .260 3.147 .002

Cross Functional

Information Sharing .367 .061 .370 5.997 .000

Technological

Engagement .427 .067 .393 6.366 .000

a. Dependent Variable: Supply Chain Agility

Model 1 indicates that relationship between Cross Functional Information Sharing and Supply

Chain Agility was positive and significant (b1=0.577, p = 0.000, Beta = 0.582). Equation 4.1

shows the regression equation for model 1, for every unit increase in Cross Functional

Information Sharing, Supply Chain Agility is predicted to increase by 0.577.

OLS Model : Supply Chain Agility= 1.803+ 0. 577Cross Functional Information Sharing

………………..equation 4.1

This implies that an increase in information pertaining Cross Functional Information Sharing

leads to increase in Supply Chain Agility amongst cosmetics manufacturing firms. The null

hypothesis that states Cross Functional Information Sharing has no significant effect on the

Supply Chain Agility was rejected at 95% signifance level. The study therefore fails to reject

the alternative hypothesis and concludes that Cross Functional Information Sharing has a

significant effect on Supply Chain Agility of Cosmetics Manufacturing Firms in the County

Government of Nairobi. Model 2 shows that the moderating effect of Technological

Engagement on the Relationship between Cross Functional Information Sharing and Supply

Chain Agility of cosmetics manufacturing firms in the county government of Nairobi, Kenya

was positive and significant (b1=0.367, p = .000, Beta = 0.321).

Equation 4.2 below shows the regression equation with the inclusion of the moderator, the

equation implies that for every unit increase in Cross Functional Information Sharing, Supply

Chain Agility is predicted to have a change of 0.367 given that Technological Engagement is

kept constant. The null hypothesis is therefore rejected at 95% significance level and it is

concluded that Technological Engagement moderates the relationship between Cross

Functional Information Sharing and Supply Chain Agility.

MMR Model : Supply Chain Agility = 0.819+ 0.367 Cross Functional Information Sharing +

0.427 Technological Engagement………………..equation 4.2 HYPOTHESIS TESTING

To test for individual significance of a coefficient, t-test was used under the null hypothesis.

The test was done at 95% level of significance (α=0.05), critical value t=1.96. The null





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hypothesis is rejected when the t-calculated is strictly greater than the t-tabulated. The

hypothesized research hypothesis for Cross Functional Information Sharing were stated as:

Ho: β2 = 0: Cross Functional Information Sharing has no significant effect on the Supply

Chain Agility of Cosmetics Manufacturing Firms in the County Government of Nairobi.

Ha: β2 ≠ 0: Cross Functional Information Sharing has a significant effect on the Supply

Chain Agility of Cosmetics Manufacturing Firms in the County Government of Nairobi

The test was done at 95% level of significance (α=0.05), critical value t=1.96. T-test statistic

was used to test for the significance of Cross Functional Information Sharing. The T value

obtained was 10.260. Comparing the t-tabulated and t-calculated values statistically, it is

evident that the t_calc > t_ α. The study therefore rejects the null hypothesis and concludes that

Cross Functional Information Sharing has a significant effect on the Supply Chain Agility of

Cosmetics Manufacturing Firms in the County Government of Nairobi.

SUMMARY OF THE FINDINGS

Cross Functional Information Sharing plays a significant role in supply chain management as

an enabler in achieving supply chain integration and agility (Gunasekaran & Ngai, 2004, Power

et al., 2010). From the findings, majority of the respondents agreed that informing supply chain

partners in advance of change in needs, exchanging of information frequently in a timely

manner and availing up-to data and information of the company to all the supply chain parties

highly affected the supply chain agility of the firms. The findings are supported by previous

works of Harisson et al.,(1999) who emphasized on the important role played by information

sharing and information technology for achieving agility. The findings reveal that the

respondents admitted that Information exchanged between them and their supply chain partners

is often reliable. Respondents were also in agreement that they keep each other informed about

events or changes that may affect the other party.

The findings further indicated that they inform their supply chain partners in advance of

changing needs. The respondents also concurred that Information exchanged between us and

our supply chain partners is often adequate. Findings also revealed that respondents were in

agreement that exchange of information takes place frequently, and/or in a timely manner. The

results indicates that there is a positive and statistically significant correlation between Cross

Functional Information Sharing and Supply Chain Agility (r=.582, p < 0.01). This is a clear

indication that any effort to improve the communications channels making it more informative

will lead to an increase in supply chain agility.

The impact of Cross-Functional information sharing on Supply Chain Agility

With the growing technological advances and the emergence of the global information

infrastructure, the companies should possess the suitable competitive inter-organizational

informational systems to enable them to achieve the rapid and effective response to the

customer needs and changing expectations (Hsu et al., 2008). The authors further argue that

firms with inadequate or insufficient information sharing will be limited in achieving the

supportive benefits from the relationships with other supply chain partners. The information

and communication tools can enable the business activities to be integrated across the whole

supply chain through the information flows which is required to coordinate the business process





27


as a whole ( Rippa,2009). Schonsleben (2000) suggest the importance of information

technologies to agility since they argue that agile companies are competing through the use of

“knowledge and competency”. Power et al., (2001) also argue that in their analysis for “less

agile” and “more agile” companies, the “more agile” companies are more willing to use high

technology. Martin and Grbac (2003) argue that Cross Functional information sharing has a

positive impact on supplier flexibility and that supplier flexibility has a positive effect on profit,

customer loyalty, and responsiveness (cited in Kannan and Tan, 2006).

DISCUSSION

Cosmetics Manufacturing Firms is a Fast Moving Consumer Goods industry and as such, the

business environment can be considered as dynamic and complex one. This has enforced the

companies working within this type of business to search for adapting agility within their

supply chains. In order to be able to achieve their goals and to respond with such high level of

uncertainty, cross functional information sharing is considered as the successful way to stay

competitive in the market place. The emphasis on the importance of information sharing and

technological tools has been also supported in a conceptual framework showing the important

characteristics for agile supply chain suggested by Harrison et al. (1999). They emphasis on

the important role played by information sharing and information technology for achieving

agility. The research provides a proposed conceptual framework showing the importance of

developing and maintaining supply chain agility within FMCGs industry. The research has

conducted its empirical study within Cosmetics Manufacturing Firms in the County

Government of Nairobi where there is little literature on this context. The research also helps

in building on the existing knowledge on supply chain agility attributes as well as on the impact

of Cross Functional Information sharing and information technology on achieving agility

within FMCGs, particularly on the Cosmetics Manufacturing firms.

Research Limitation

As this research has its own contributions, it has also some limitations. First, the conceptual

framework was generated from a cross sectional survey of Cosmetics Manufacturing Firms

found in one county only, which is the County Government of Nairobi, Kenya. This is a

FMCGs industry and therefore the research results can’t be generalized in other types of

industries, such as the service sector. Therefore future research is needed to explore other

supply chain agility attributes in other counties as well as in other types of business, industries

as well as service sector. Interesting findings might be obtained from studies that explore

integral relationship strategies in other industries or settings. Like for instance, further

qualitative research could be conducted in supply chains of different types. This would help to

validate and improve the generalizability of the findings.

CONCLUSION

Nowadays businesses have to possess means to meet rapid market changes in an effective

manner to satisfy its customers. Agility has been introduced to be applied to the supply chain

context to enable the business entity to face the business environmental changes and to deal

with them. Agility can enable the business entity to be differentiated from other competitors as

competition has been very high and especially after globalization. From this point, this paper





28


contributes to the existing literature by emphasizing on the importance of Cross-Functional

Information Sharing on implementing high level of agility within Fast Moving Consumer

Goods industry, such as Cosmetics Manufacturing Firms. This is particularly true especially

when screening at the industry as well as its required attributes for the applying of agility within

the supply chain of such type of industry. Cross functional information systems are seen to

assume a fundamental role in developing Supply Chain Agility. IT plays a key role in the

integration of processes, for instance synchronizing suppliers in the network by providing real

time information. Therefore the study concludes that Cross functional information sharing is a

pertinent factor as it affects the Supply Chain Agility of Firms.

The research has managerial implications as it provides guidance for the Cosmetics

Manufacturing Companies, particularly those in the developing countries like Kenya, and

especially those working within FMCGs industry to the importance of Cross functional

information sharing as an antecedent to Supply Chain Agility. The attribute derived from this

research can be considered as a checklist for companies to determine the required attributes

necessary for achieving agility within their supply chain.

The study recommends that firms should focus more on Supply Chain Technologies because

these technologies enable supply chain members to make real-time decisions which could

impact the cost structure and ultimately the competitive position of the firm.

REFERENCES

Christopher , M., & Juttner, U. (2000). Supply chain relationships: Making Transition to

Closer Integration. International Journal of Logistics Research and Applications: A

Leading Journal of supply chain Management, 3(1), 5-23.

Fawcett, S., Magnan, G., & McCarter, M. (2008). A Three-Stage Implementation Model For

Supply Chain Collaboration. Journal of Business Logistics, 29(1), 93.

Flint, D. J. (2004). Strategic Marketing in Global Supply Chains: Four Challenges. Industrial

Marketing Management, 33(1), 45-50.

Gunasekaran, A., & Yusuf, Y. (2002). Agile Manufacturing: A Taxonomy of Strategic and

Technological Imperatives. International Journal of Production Research, 40(6),

13571385.

Hervani, A. A., Helms, M. M., & Sarkis, J. (2005). Performance Measurement For Green

Supply Chain Management. Benchmarking: An International Journal, 12(4), 330-353.

Hsu, C., Kannan, V., Tan, K., & Leong, K. (2008). Information Sharing, Buyer-Supplier

Relationships and Firms Purchasing Performance. International Journal of Physical

Distribution and Logistics, 38(4), 296-310.

Journal of the Association For Information Sysytems, 13(3), 150-171.

Kaefer, F., & Bendoly, E. (2004). Measuring the Impact of Organizational Constraints on the

Success of Business-To-Business E-Commerce Efforts. Information and Management,

41(5), 529-541.

Kisperska-Moron, D., & De Haan, J. (2011). Improving Supply Chain Performance to Satisfy

Final Customers: Leagile Experiences of a Polish Distributor. International Journal of

Production Economics, 133(1), 127-134.

Li, S., & Lin, B. (2006). Accessing Information Sharing and Information Quality in Supply

Chain Management. Decision Support Systems, 42(3), 1641-1656.





29


Mentzer, J. T., De Witt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z.

G. (2001). Defining Supply Chain Management. Journal of Business Logistics, 17(1),

1-25.

Narasimhan, R., & Das, A. (1999). Manufacturing Agility and Supply Chain Management

Practices. production and Inventory Management Journal, 40(1), 10-15.

Nazir, S., & Pinsonneault, A. (2012). IT and Firm Agilty: An Electronic Integration

Perspective.

Ngai, E. W., Chau, D. C., & Chan, T. A. (2011). Information Technology, Operational and

Management Competences For Supply Chain Agility: Findings from Case Studies.

Journal of Strategic Information Systems, 20(3), 232-249.

Paulraj, A., Lado, A. A., & Chen, I. J. (2008). Inter-Organizational Communication as a

Relational Competency: Antecedents and Performance Outcomes in Collaborative

Buyer-Supplier Relationships. Journal of Operations Management, 26(1), 45-64.

Prajogo, D., & Olhager, J. (2012). Supply Chain Integration and Performance: The Effects of

Long-Term Relationships, Information Technology and Sharing and Logistics

Integration. International Journal of ProductionEconomics, 135(1), 514-522.

Premkumar, G., Ramamurthy, K., & Saunders, C. S. (2005). Information Processing View of

Organizations: An Exploratoty Examination of Fit in the Context of Inter-

Organizational Relationships. Journal of Management Information Systems, 22(1), 257-

294.

Sanders, N. R. (2008). Pattern of Information technology Use: The Impact on Buyer-supplier

Coordination and performance. Journal of Operations Management, 26(3), 349-367.

Sekaran, U., & Bougie, R. (2010). Research Methods For Business: A Skill Building

Approach. London: Wiley.

Supply Chain. International Journal of Operations and Production Management, 21(1/2),

126-147.

Van Hoek, R. I., Harrison, A., & Christopher, M. (2001). Measuring Agile Capabilities in the

Vonderembse, M., Uppal, M., Huang, S. H., & Dismukes, J. P. (2006). Designing Supply

Chains: Towards Theory Development. International Journal of Production

Economics, 100(2), 223-238.

White, A., & Daniel, E. (2005). The Role of Emergent Information Technologies and

Systems in Enabling Supply Chain Agility. International Journal of Information

Management, 25(5), 396-410.

Wu, K., & Ouyang, L. (2003). An Integrated Single-Vendor Single Buyer Inventory System

with shortage derived Algebraically. Production Planning Control, 14(6), 555-561.

Yamane, T. (1967). Statistics: An Introductory Analysis. New York: Harper and Row.

Yusuf , Y. Y., Gunasekaran, A., Adeleye, E. O., & Sivayoganathan, K. (2004). Agile Supply

Chain Capabilities: Determinants of Competitive Objectives. European Journal of

Operations Research, 159(2), 379-392.

Yusuf, Y. Y., Sarhadi, M., & Gunasekaran, A. (1999). Agile Manufacturing: The Drivers,

Concepts and Attributes. International Journal of Production Economics, 62(1/2), 33-

43.


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